ABSTRACT
In settings with zero community transmission, any new SARS-CoV-2 outbreaks are likely to be the result of random incursions. The level of restrictions in place at the time of the incursion is likely to considerably affect possible outbreak trajectories. We used an agent-based model to investigate the relationship between ongoing restrictions and behavioural factors, and the probability of an incursion causing an outbreak and the resulting growth rate. We applied our model to the state of Victoria, Australia, which has reached zero community transmission as of November 2020. We found that a future incursion has a 45% probability of causing an outbreak (defined as a 7-day average of >5 new cases per day within 60 days) if no restrictions were in place, decreasing to 23% with a mandatory masks policy, density restrictions on venues such as restaurants, and if employees worked from home where possible. A drop in community symptomatic testing rates was associated with up to a 10-percentage point increase in outbreak probability, highlighting the importance of maintaining high testing rates as part of a suppression strategy. Because the chance of an incursion occurring is closely related to border controls, outbreak risk management strategies require an integrated approaching spanning border controls, ongoing restrictions, and plans for response. Each individual restriction or control strategy reduces the risk of an outbreak. They can be traded off against each other, but if too many are removed there is a danger of accumulating an unsafe level of risk. The outbreak probabilities estimated in this study are of particular relevance in assessing the downstream risks associated with increased international travel.
ABSTRACT
AimsWe assessed COVID-19 epidemic risks associated with relaxing a set of physical distancing restrictions in the state of Victoria, Australia - a setting with low community transmission - in line with a national framework that aims to balance sequential policy relaxations with longer-term public health and economic need. MethodsAn agent-based model, Covasim, was calibrated to the local COVID-19 epidemiological and policy environment. Contact networks were modelled to capture transmission risks in households, schools and workplaces, and a variety of community spaces (e.g. public transport, parks, bars, cafes/restaurants) and activities (e.g. community or professional sports, large events). Policy changes that could prevent or reduce transmission in specific locations (e.g. opening/closing businesses) were modelled in the context of interventions that included testing, contact tracing (including via a smartphone app), and quarantine. ResultsPolicy changes leading to the gathering of large, unstructured groups with unknown individuals (e.g. bars opening, increased public transport use) posed the greatest risk, while policy changes leading to smaller, structured gatherings with known individuals (e.g. small social gatherings) posed least risk. In the model, epidemic impact following some policy changes took more than two months to occur. Model outcomes support continuation of working from home policies to reduce public transport use, and risk mitigation strategies in the context of social venues opening, such as >30% population-uptake of a contact-tracing app, physical distancing policies within venues reducing transmissibility by >40%, or patron identification records being kept to enable >60% contact tracing. ConclusionsIn a low transmission setting, care should be taken to avoid lifting sequential COVID-19 policy restrictions within short time periods, as it could take more than two months to detect the consequences of any changes. These findings have implications for other settings with low community transmission where governments are beginning to lift restrictions.
ABSTRACT
Introduction@#Students comprised the majority of early cases of influenza A(H1N1)pdm09 in Melbourne, Australia. Students and school settings were targeted for public health interventions following the emergence of pH1N1. This study was conducted to describe changes in social contacts among the earliest confirmed student cases of pH1N1 in Melbourne, Australia, to inform future pandemic control policy and explore transmission model assumptions@*Methods@#A retrospective cross-sectional behavioural study of student cases with laboratory-confirmed pH1N1 between 28 April and 3 June 2009 was conducted in 2009. Demographics, symptom onset dates and detailed information on regular and additional extracurricular activities were collected. Summary measures for activities were calculated, including median group size and median number of close contacts and attendance during the students' exposure and infectious periods or during school closures. A multivariable model was used to assess associations between rates of participation in extracurricular activities and both school closures and students' infectious periods.@*Results@#Among 162 eligible cases, 99 students participated. Students reported social contact in both curricular and extra-curricular activities. Group size and total number of close contacts varied. While participation in activities decreased during the students' infectious periods and during school closures, social contact was common during periods when isolation was advised and during school closures. @*Discussion@#This study demonstrates the potential central role of young people in pandemic disease transmission given the level of non-adherence to prevention and control measures. These finding have public health implications for both informing modelling estimates of future pandemics and targeting prevention and control strategies to young people.
